Fuzzy Rule-Based Model to Train Videos in Video Surveillance System

Manju, A.; Revathi, A.; Arivukarasi, M.; Hariharan, S.; Umarani, V.; Chen, Shih‐Yu; Wang, Jin

doi:10.32604/iasc.2023.038444

Cited by 1 publication

(1 citation statement)

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“…In previous research, various techniques have been explored to enhance the performance of fuzzy rule-based classifiers (Huang et al, 2022) (Aghaeipoor et al, 2023) (Manju et al, 2023). One such approach is the integration of hybrid grid partitioning and rough set theory (Buabeng et al, 2022) (Tran & Huh, 2022).…”

Section: Introductionmentioning

confidence: 99%

An integrated approach for fuzzy rule generation in dataset classification using hybrid grid partitioning and rough set theory

Ferguson

2023

emod

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This research presents an integrated approach for fuzzy rule generation in dataset classification by combining hybrid grid partitioning and rough set theory. The objective is to enhance the accuracy and interpretability of classification models. The approach leverages hybrid grid partitioning to achieve localized rule generation, capturing the local characteristics and patterns within different regions of the feature space. Furthermore, rough set theory is applied for attribute reduction, identifying the most relevant features and reducing the complexity of the classification problem. The generated fuzzy rules provide interpretable and understandable classification rules that facilitate domain expert interpretation. The research contributes to the field by proposing a comprehensive framework that improves both accuracy and interpretability of dataset classification. The findings demonstrate the effectiveness of the integrated approach, although certain limitations exist. Future research should focus on parameter selection, scalability challenges, and the applicability of the approach to diverse problem domains. The integrated approach presents a promising methodology for enhancing the accuracy and interpretability of dataset classification, with potential applications in various domains where accurate and interpretable classification models are crucial.

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Section: Introductionmentioning

confidence: 99%

An integrated approach for fuzzy rule generation in dataset classification using hybrid grid partitioning and rough set theory

Ferguson

2023

emod

View full text Add to dashboard Cite

show abstract

Fuzzy Rule-Based Model to Train Videos in Video Surveillance System

Cited by 1 publication

References 20 publications

An integrated approach for fuzzy rule generation in dataset classification using hybrid grid partitioning and rough set theory

An integrated approach for fuzzy rule generation in dataset classification using hybrid grid partitioning and rough set theory

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